2. Orientation¶

This orientation assumes you have already opened the training environment by clicking on the "Open in GitHub Codespaces" button. If not, please do so now, ideally in a second browser window or tab so you can refer back to these instructions.

2.1 GitHub Codespaces¶

The GitHub Codespaces environment contains all the software, code and data necessary to work through this training course, so you don't need to install anything yourself. However, you do need a (free) GitHub account to log in, and you should take a few minutes to familiarize yourself with the interface.

If you have not yet done so, please go through the Environment Setup mini-course before going any further.

2.2 Working directory¶

Throughout this training course, we'll be working in the small_nextflow/ directory.

Change directory now by running this command in the terminal:

cd small_nextflow/

Tip

If for whatever reason you move out of this directory, you can always use the full path to return to it, assuming you're running this within the GitHub Codespaces training environment:

cd /workspaces/training/small_nextflow

Now let's have a look at the contents of this directory.

2.3 Materials provided¶

You can explore the contents of this directory by using the file explorer on the left-hand side of the training workspace. Alternatively, you can use the ls command.

Here we list the contents of the directory:

ls -la

If you run this inside small_nextflow, you should see a minimal directory structure:

Directory contents

.
├── .stuff/
    ├── cat_me.sh
    ├── classify.py
    └── pyproject.toml

Here's a summary of what you should know to get started:

The .stuff/ directory contains helper scripts and configuration files we'll use throughout the workshop. You can think of this as a toolbox we'll pull from as we build our workflow.
The cat_me.sh script fetches random cat images from an API for our workflow to process.
The classify.py script is a Python program that uses machine learning to classify images.
The pyproject.toml file describes the Python dependencies needed for the classification script.

Throughout this workshop, we'll start with this minimal setup and progressively build a complete image classification workflow.

Let's get started by creating a fresh, empty main.nf:

code main.nf

Now, to begin the course, click on the arrow in the bottom right corner of this page.